Coronary Artery Disease (CAD) and heart-related problems and cardiac arrhythmias are serious illnesses. A 12-lead electrocardiogram (ECG) and multi-channel intra-cardiac electrograms (ICEG) provide diagnostic reference standards and criteria for evaluating cardiac rhythm and events. Currently waveform morphologies and time domain parameter analysis, such as P wave, QRS complex, ST segment, T wave, are used for cardiac arrhythmia monitoring and identification, such as atrial fibrillation (AF), myocardial ischemia (MI) and ventricular tachycardia/fibrillation (VT/VF), for example. However, the waveform morphologies and time domain parameter analysis are sometimes subjective and time-consuming, and require extensive expertise and clinical experience for accurate interpretation and proper cardiac rhythm management.
Some known systems apply more sophisticated mathematical theories to biomedical signal interpretation, such as frequency analysis, symbolic complexity analysis and signal entropy evaluation. But such known systems typically focus on generating a new pathology index for qualitative cardiac arrhythmia characterization, in which the data variance and statistical characteristics of the time varying signals (ECG and ICEG) have not been determined, diagnosed and evaluated. Additionally, cardiac electrophysiological (EP) activities and signals (ECG and ICEG) are time varying and known signal calculation and related analysis usually fails to localize a malfunction severity and trend of cardiac events (e.g., myocardial ischemia and infarction), such as cardiac pathology irregularity stages, arrhythmia occurrence and drug delivery response, for example.
Further, known system diagnosis and interpretation of cardiac signals based on an electrophysiological signal waveform and morphology require extensive clinical knowledge and experience. Inaccurate and subjective evaluation and diagnosis may cause unexpected delay in cardiac rhythm management, such as drug delivery and emergency treatment. Known system diagnosis and evaluation of a cardiac signal typically uses time domain parameters to diagnose and evaluate myocardial events, such as ST segment voltage deviation for ischemia detection (e.g. 0.1 mV elevation is a clinical standard for myocardial ischemia (MI) detection). However this MI analysis only works for surface ECG signals, but not for intracardiac electrograms and the ST segment deviation (voltage) cannot be utilized as a quantitative method for myocardial ischemia severity diagnosis and characterization. ST segment analysis in known clinical applications detects and evaluates MI or infarction events using a repolarization procedure signal portion within a heart beat. Information concerning a depolarization procedure is not efficiently utilized in known systems for ischemia and infarction characterization which depend on patient responses (such as chest pain, discomfort) using signal recordings and physician interpretation, however, there are many ischemia and infarction cases which are non-symptomatic. A system according to invention principles addresses these deficiencies and associated problems.